Modified Exponential Model-based Capacity Estimation and RUL Prediction for Lithium-ion Batteries
In response to the complexity of the aging path of lithium-ion batteries and the inadequacy of conventional em-pirical models to accurately track the battery capacity decay trajectory,this paper proposes a battery capacity estimation and remaining useful life (RUL)prediction model that combines a three-exponential model and particle filter algorithm. First a three-exponential model capable of describing different aging battery capacity decay trajectories is established.Sec-ond the particle filter algorithm is employed to estimate the parameters of the three-exponential model.Finally the predic-tive results of the proposed model are compared and analyzed with those of two empirical models using NASA and CACLE datasets.Experimental results indicate that the proposed model achieves MAE and RMSE values within 0.0058 and 0.0098,respectively,demonstrating superior predictive utility to the other two empirical models,and hence exhibits high-er accuracy and robustness.
lithium-ion batteryempirical modelthree-exponential modelparticle filter algorithmremaining useful life
万方数据
维普
